Method and apparatus for automatically categorizing images in a digital camera

ABSTRACT

A method and apparatus for automatically categorizing images in a digital camera is provided. In one aspect, a digital camera includes a processor that converts raw image data into processed image data at the time of image capture, an analysis module coupled to the processor that analyzes the raw image data at the time of image capture and identifies one or more categories to which each of the images may relate, and category tags that are attached to and stored in each of the images corresponding to the categories. By attaching and storing the category tags with each of the images, the processor can automatically sort the images by their respective categories.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 09/430,235, entitled “Method and Apparatus for Managing ImageCategories in a Digital Camera to Enhance Performance of a High-CapacityImage Storage Media,” (P153CIP) filed on Oct. 29, 1999, now issued asU.S. Pat. No. 6,914,625, which is a continuation-in-part of U.S. patentapplication Ser. No. 09/121,760 filed on Jul. 23, 1998, entitled “Systemand Method for Automatic Analysis and Categorization of Images in anElectronic Imaging Device,” (P153CPA) now abandoned, each assigned tothe assignee of the present application.

FIELD OF THE INVENTION

This invention relates generally to electronic data processing, andrelates more particularly to a system and method for the automaticanalysis and categorization of images in an electronic imaging device.

BACKGROUND OF THE INVENTION

The efficient manipulation of captured image data is a significantconsideration for designers, manufacturers, and users of electronicimaging devices. Contemporary imaging devices such as digital cameraseffectively enable users to capture images, assemble or edit thecaptured images, exchange the captured images electronically, or print ahard copy of the captured images. users to capture images, assemble oredit the captured images, exchange the captured images electronically,or print a hard copy of the captured images.

As a camera user captures a number of digital images, it typicallybecomes necessary to sort and categorize the digital images. In somesystems, a camera user must resort to the cumbersome and time-consumingtask of individually viewing each captured image, identifying variousgroupings of image categories, and somehow manually tagging each imageto specify the particular image category. For example, in Parulski, U.S.Pat. No. 5,633,678, a camera user manually selects a category for agroup of images prior to the capture of the images. The camera user mustselect a new category for each new group of images. Such a manualcategorization system is awkward to use and, therefore, does not provideas efficient an imaging device as a camera that features an automaticcategorization system.

In other systems, software programs are available to permit the user tocreate thumbnails (smaller renditions of the captured image) and toplace the thumbnails, with references to the original images, intovarious libraries or category systems. This process may also become verytime consuming, especially as the number of captured images or thevariety of category types increases.

From the preceding discussion, it becomes apparent that an electronicimaging system that manually analyzes and categorizes any significantnumber of captured images does not achieve an acceptable degree ofefficiency. Therefore, an electronic imaging device that automaticallyanalyzes captured images, and then responsively categorizes the analyzedimages into one or more selected image groupings, would clearly providea significant improvement in efficient functionality for variouscontemporary electronic imaging technologies.

For all the foregoing reasons, an improved system and method are neededfor the automatic analysis and categorization of images in an electronicimaging device.

SUMMARY OF THE INVENTION

A method and apparatus for automatically categorizing images in adigital camera is provided. In one aspect, a digital camera includes aprocessor that converts raw image data into processed image data at thetime of image capture, an analysis module coupled to the processor thatanalyzes the raw image data at the time of image capture and identifiesone or more categories to which each of the images may relate, andcategory tags that are attached to and stored in each of the imagescorresponding to the categories. By attaching and storing the categorytags with each of the images, the processor can automatically sort theimages by their respective categories.

In the preferred embodiment, after the image data is converted into RGBformat, selected analysis modules may connect through an RGB insertionpoint to advantageously analyze the image data at an RGB transitionpoint, in accordance with the present invention. Once a particularanalysis module analyzes the final line of the image data, then thatanalysis module preferably generates any appropriate category tags andstores the generated category tags into a blank category tag location inthe image file. The digital camera may then subsequently access thestored category tags to automatically categorize and utilize theindividual stored images (which each correspond to a separate imagefile).

Next, another image processing module preferably performs gammacorrection and color space conversion on the image data. The imageprocessing module also preferably converts the color space format of theimage data. In the preferred embodiment, the image data is convertedinto YCC 444 format.

After the image data is converted into YCC 444 format, selected analysismodules may be plugged into a YCC insertion point to analyze the imagedata at a YCC transition point, in accordance with the presentinvention. As discussed above, once a particular analysis moduleanalyzes the final line of the image data, then that analysis modulepreferably generates any appropriate category tags and stores thegenerated category tags into a blank category tag location in the imagefile for subsequent use by the camera to automatically categorizecaptured images. In other embodiments of the present invention, analysismodules may readily analyze image data at any other time or insertionpoint within the camera.

Next, an image processing module preferably performs a sharpeningprocedure on the image data, and also may perform a variety of otherprocessing options. Then, an image processing module preferablydecimates the image data, and the image data is compressed into a finalimage format (preferably JPEG.) Next, a file formatter preferablyformats the compressed image file, and the resulting image file isfinally saved into a removable memory device.

The image file thus includes any appropriate category tags, and thecamera may then subsequently utilize the category tags to automaticallyaccess selected images, in accordance with the present invention. Thepresent invention therefore provides an efficient system and method forautomatically analysis and categorization of captured images in anelectronic imaging device.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of one embodiment for a digital camera,according to the present invention;

FIG. 2 is a block diagram of one embodiment for the imaging device ofFIG. 1, according to the present invention;

FIG. 3 is a block diagram including one embodiment for a cameracomputer;

FIG. 4 is a rear elevation view of one embodiment for the FIG. 1 digitalcamera;

FIG. 5 is a diagram one embodiment for the non-volatile memory of FIG.3, according to the present invention;

FIG. 6 is a diagram of one embodiment for the dynamic random-accessmemory of FIG. 3, according to the present invention;

FIG. 7 is a diagram of one embodiment for a single analysis module ofFIG. 6, according to the present invention;

FIG. 8 is a diagram of one embodiment for an image file, in accordancewith the present invention;

FIG. 9 is a diagram of one embodiment for the image tags of FIG. 8; and

FIG. 10 is a flowchart for one embodiment of method steps toautomatically analyze and categorize images, according to the presentinvention.

DESCRIPTION OF THE INVENTION

The present invention relates to an improvement in digital imagingdevices, including digital cameras. The following description ispresented to enable one of ordinary skill in the art to make and use theinvention and is provided in the context of a patent application and itsrequirements. Although the present invention will be described in thecontext of a digital camera, various modifications to the preferredembodiment will be readily apparent to those skilled in the art and thegeneric principles herein may be applied to various other embodiments.That is, any imaging device, which captures image data, couldincorporate the features described hereinbelow and that device would bewithin the spirit and scope of the present invention. Thus, the presentinvention is not intended to be limited to the embodiment shown, but isto be accorded the widest scope consistent with the principles andfeatures described herein.

The present invention comprises one or more analysis modules thatexamine captured image files for selected criteria. The analysis modulesthen responsively generate and store appropriate category tags alongwith the image file to advantageously enable the imaging device tosubsequently access the stored category tags and thereby automaticallyaccess desired categories of captured images.

Referring now to FIG. 1, a block diagram of one embodiment for a digitalcamera 110 is shown. Camera 110 preferably comprises an imaging device114, a system bus 116, and a camera computer 118. Imaging capture device114 may be optically coupled to an object 112 and electrically coupledvia system bus 116 to camera computer 118. Once a user has focusedimaging capture device 114 on object 112 and instructed camera 110 tocapture an image of object 112, camera computer 118 commands imagingcapture device 114 via system bus 116 to capture raw image datarepresenting object 112. The captured raw image data is transferred oversystem bus 116 to camera computer 118, which performs variousimage-processing functions on the image data. System bus 116 also passesvarious status and control signals between imaging capture device 114and camera computer 118.

Referring now to FIG. 2, a block diagram of one embodiment for imagingdevice 114 of FIG. 1 is shown. Imaging device 114 preferably comprises alens 220 having an iris (not shown), a filter 222, an image sensor 224,a timing generator 226, an analog signal processor (ASP) 228, ananalog-to-digital (A/D) converter 230, an interface 232, and one or moremotors 234 to adjust focus of lens 220.

Imaging capture device 114 captures an image of object 112 via reflectedlight impacting image sensor 224 along optical path 236. Image sensor224, which is preferably a charged-coupled device (CCD), responsivelygenerates a set of raw image data in CCD format representing thecaptured image 112. The raw image data is then routed through ASP 228,A/D converter 230, and interface 232. Interface 232 has outputs forcontrolling ASP 228, motors 234 and timing generator 226. From interface232, the raw image data passes over system bus 116 to camera computer118.

Referring now to FIG. 3, a block diagram of one embodiment for cameracomputer 118 of FIG. 1 is shown. System bus 116 provides communicationbetween imaging capture device 114, electrically-erasable programmableread-only memory (EEPROM) 341, optional power manager 342, centralprocessing unit (CPU) 344, dynamic random-access memory (DRAM) 346,camera input/output (I/O) 348, non-volatile memory 350, andbuffers/connector 352. Removable memory 354 connects to system bus 116via buffers/connector 352. In alternate embodiments, camera 110 may alsoreadily be implemented without removable memory 354 or buffers/connector352.

Power manager 342 communicates with power supply 356 and coordinatespower management operations for camera 110. CPU 344 preferably includesa processor device for controlling the operation of camera 110. In thepreferred embodiment, CPU 344 is capable of concurrently runningmultiple software routines to control the various processes of camera110 within a multi-threading environment. DRAM 346 is a contiguous blockof dynamic memory, which may be selectively allocated to various storagefunctions. LCD controller 390 accesses DRAM 346 and transfers processedimage data to LCD screen 302 for display.

Camera I/O 348 is an interface device allowing communications to andfrom camera computer 118. For example, camera I/O 348 permits anexternal host computer (not shown) to connect to and communicate withcamera computer 118. Camera I/O 348 may also interface with a pluralityof buttons and/or dials 304, and an optional status LCD 306, which, inaddition to LCD screen 302, are the hardware elements of the camera'suser interface 308.

Non-volatile memory 350, which preferably comprises a conventionalread-only memory or flash memory, stores a set of computer-readableprogram instructions to control the operation of camera 110. Removablememory 354 serves as an additional image data storage area and ispreferably a non-volatile device, readily removable and replaceable by acamera user via buffers/connector 352. Thus, a user who possessesseveral removable memories 354 may replace a full removable memory 354with an empty removable memory 354 to effectively expand thepicture-taking capacity of camera 110. In the preferred embodiment ofthe present invention, removable memory 354 is preferably implementedusing a flash disk.

Power supply 356 provides operating power to the various components ofcamera 110 via main power bus 362 and secondary power bus 364. The mainpower bus 362 provides power to imaging capture device 114, camera I/O348, non-volatile memory 350 and removable memory 354, while secondarypower bus 364 provides power to power manager 342, CPU 344 and DRAM 346.

Power supply 356 is connected to main batteries 358 and also to backupbatteries 360. Camera 110 user may also connect power supply 356 to anoptional external power source. During normal operation of power supply356, main batteries 358 provide operating power to power supply 356which then provides the operating power to camera 110 via both mainpower bus 362 and secondary power bus 364. During a power failure modewhere main batteries 358 have failed (i.e., when their output voltagehas fallen below a minimum operational voltage level), backup batteries360 provide operating power to power supply 356 which then providesoperating power only to the secondary power bus 364 of camera 110.

Referring now to FIG. 4, a rear elevation view of one embodiment forcamera 110 of FIG. 1 is shown. The FIG. 4 representation depictshardware components of user interface 308 of camera 110, showing LCDscreen 302, user interface 308, a four-way navigation control button409, an overlay button 412, a menu button 414, and a set of programmablesoft keys 416.

User interface 308 includes several operating modes for supportingvarious camera functions. In the preferred embodiment, operating modesmay include capture mode, review mode, play mode, and PC-connect mode.Within capture mode, menu options are available to set-up the categoriesused during image capture. The user preferably switches between thecamera modes by selecting a mode dial (not shown).

Referring now to FIG. 5, a diagram one embodiment for the non-volatilememory 350 of FIG. 3 is shown. The FIG. 5 diagram includes controlapplication 500, toolbox 502, drivers 504, kernel 506, and systemconfiguration 508. Control application 500 comprises programinstructions for controlling and coordinating the various functions ofcamera 110. Toolbox 502 contains selected function modules includingimage processing backplane 510, image processing modules 512, menu anddialog manager 514, and file formatter 516.

Image processing backplane 510 includes software routines thatcoordinate the functioning and communication of various image processingmodules 512 and handle the data flow between the various modules. Imageprocessing modules 512 preferably include selectable plug-in softwareroutines that manipulate captured image data in a variety of ways,depending on the particular modules selected. Menu and dialog manager514 includes software routines which provide information for controllingaccess to camera control menus and camera control menu items for accessto features in camera 110. File formatter 516 includes software routinesfor creating an image file from the processed image data.

Drivers 504 control various hardware devices within camera 110 (forexample, motors 234). Kernel 506 provides basic underlying services forthe camera 110 operating system. System configuration 508 performsinitial start-up routines for camera 110, including the boot routine andinitial system diagnostics.

Now referring to FIG. 6, a diagram of one embodiment for dynamicrandom-access-memory (DRAM) 346 is shown. DRAM 346 includes RAM disk532, system area 534, analysis modules 540 and working memory 530.

1 In the preferred embodiment, RAM disk 532 is a memory area used forstoring raw and compressed image data and is organized in a “sectored”format similar to that of conventional hard disk drives. A conventionaland standardized file system permits external host computer systems, viaI/O 348, to recognize and access the data stored on RAM disk 532. Systemarea 534 stores data regarding system errors (e.g., why a systemshutdown occurred) for use by CPU 344 to restart computer 118.

Working memory 530 includes stacks, data structures and variables usedby CPU 344 while executing the software routines used within cameracomputer 118. Working memory 530 also includes input buffers 538 forinitially storing sets of image data received from imaging device 114for image conversion, and frame buffers 536 for storing data to displayon LCD screen 302.

In accordance with the present invention, analysis modules 540preferably each include one or more software routines for automaticallyanalyzing and categorizing images. In the FIG. 6 embodiment, analysismodules 540 may be loaded into RAM 346 from removable memory 354 oranother external source. Analysis modules 540 further discussed below inconjunction with FIGS. 7 through 10.

Referring now to FIG. 7, a diagram of one embodiment for a singleanalysis module 540 of FIG. 6 is shown. Analysis module 540 includestext category list 610, combination logic 615, analysis algorithms 630,and parametric control 635.

Text category list 610 is a listing of the various possible imagecategories available for a given analysis module 540. Combination logic615 determines how to resolve the results of the image analysis whenmultiple analysis algorithms 630 are utilized. Parametric control 635 isused to control settable parameters for analysis module 540. Forexample, analysis module may be turned on/off, or sensitivity settingsfor analysis module 540 may be controlled with parametric control 635.

Analysis algorithms 630 are a series of software routines ranging fromanalysis algorithm 1 (620) through analysis algorithm n (625.) Analysisalgorithms 630 are each designed to allow analysis module 540 to accessand analyze images at various stages in the processing chain of camera110, in order to gather information about the image for latercategorization.

Typically, each analysis algorithm 630 is designed to detect at leastone image category. For example, individual analysis algorithms 630 maybe designed to detect a person or groups of people based oncharacteristics like substantial amounts of flesh tones within theimage. Individual analysis algorithms 630 may likewise be designed todetect nature scenes from characteristics like substantial green contentin the image combined with the relative lack of hard edges. Similarly,categories like city images, water images or indoor images may bedetected by characteristic features contained in those images. Once thelast line of image data from a given image is processed, analysis module540 then preferably generates one or more category tags that correspondto the particular image, and the generated category tags are stored aspart of the image file. A user of camera 110 may thus readily utilizethe category tags to efficiently access and sort images into selectedcategories.

Referring now to FIG. 8, a diagram of one embodiment for an image file835 is shown, in accordance with the present invention. In the FIG. 8embodiment, image file 835 includes a header 805, image data 810, ascreennail 815, a thumbnail 820, and image tags 825.

Header 805 preferably includes information that identifies and describesthe various contents of image file 835. Image data 810 contains actualcaptured image data. Image data 810 exists in whichever format that isappropriate for the current location of image file 835 within the imageprocessing chain of camera 110. Screennail 815 and thumbnail 820 areeach different versions of image data 810 that have varying degrees ofreduced resolution for a number of special viewing applications.

Image tags 825 includes various types of information that correspond andrelate to particular captured image data 810. Image tags 825 are furtherdiscussed below in conjunction with FIG. 9.

Referring now to FIG. 9, a diagram of one embodiment for the image tagsof FIG. 8 is shown. In the FIG. 9 embodiment, image tags 825 includecapture information tags 710, user tags 715, product tags 720, andcategory tags 735.

Capture information tags 710 preferably include various types ofinformation that correlate with the captured image data 810 (FIG. 8).For example, capture information tags 710 may indicate focus setting,aperture setting, and other relevant information that may be useful foreffectively processing or analyzing the corresponding image data 810.User tags 715 and product tags 720 typically contain various otherinformation that may be needed for use with camera 110.

Category tags 735 are each preferably generated by analysis modules 540after analysis modules 540 individually examine image data 810 fromimage file 835, in accordance with the present invention. Camera 110 maythus advantageously access and utilize category tags 735 to identify oneor more categories to which a given set of image data 810 may likelyrelate. As discussed above in conjunction with FIG. 7, category tags 735may correspond to a wide variety of possible image categories. In thepreferred embodiment, image tags 825 initially contains sixteen emptylocations to which various analysis modules 540 may write appropriatecategory tags 735 for automatically categorizing the corresponding imagedata 810, in accordance with the present invention.

Referring now to FIG. 10, a flowchart is shown for one embodiment ofmethod steps to automatically analyze and categorize images, accordingto the present invention. FIG. 10 also details the operation of a seriesof plug-in image processing modules 512 for processing and formattingimage data 810. However, in other embodiments of camera 110, variousother modules may readily be substituted or added to those modulesdiscussed in below conjunction with the FIG. 10 embodiment.

Initially, in step 910, camera 110 preferably captures a selected imageas CCD raw data, stores the raw data as image data 810 into image file835, and then propagates image file 835 through camera 110 forprocessing and formatting of the image data 810. In step 920, an imageprocessing module 512 preferably replaces any defective pixels in imagedata 810, and also performs white balance and color correction on imagedata 810.

Next, in step 925, another image processing module 512 preferablyperforms interpolation (edge enhancement) on image data 810, and thenconverts image data 810 into an intermediate format. In the preferredembodiment, step 925 converts image data 810 into an RGB (Red, Blue,Green) format.

In the FIG. 10 embodiment, following step 925, selected analysis modules540 may be plugged into an RGB insertion point 940 to advantageouslyanalyze image data 810 at RGB transition point 930, in accordance withthe present invention. One, some, or all of the analysis modules 540 mayanalyze image data 810 at RGB transition point 930. Preferably, analysismodules 540 are selected for optimal compatibility and effectivenesswith the current format of image data 810 at RGB transition point 930.Once a particular analysis module 540 analyzes the final line of imagedata 810, then that analysis module 540 preferably generates anyappropriate category tags 735 and stores the generated category tags 735into a blank category tag location in image file 835. Then, camera 110may subsequently access the stored category tags 735 to automaticallycategorize and utilize the individual stored images (which eachcorrespond to a separate image file 835).

Next, in step 945, another image processing module 512 preferablyperforms gamma correction and color space conversion on image data 810.During step 945, the image processing module 512 also preferablyconverts the color space format of image data 810. In the FIG. 10embodiment, image data 810 is converted to YCC 444 (Luminance,Chrominance-red, and Chrominance-blue) format.

In the FIG. 10 embodiment, following step 945, selected analysis modules540 may be plugged into a YCC insertion point 960 to analyze image data810 at YCC transition point 950, in accordance with the presentinvention. One, some, or all of the analysis modules 540 may analyzeimage data 810 at YCC transition point 950. As discussed above, once aparticular analysis module 540 analyzes the final line of image data810, then that analysis module 540 preferably generates any appropriatecategory tags 735 and stores the generated category tags 735 into ablank category tag location in image file 835 for subsequent use bycamera 110 to automatically categorize captured images.

This discussion of the FIG. 10 embodiment specifically refers only RGBinsertion point 940 and YCC insertion point 960. However, in otherembodiments of the present invention, analysis modules 540 may readilyanalyze image data 810 at any other time or insertion point withincamera 110. For example, in an alternate embodiment, analysis modules540 may readily be configured to examine image data 810 at capture time,and to specifically recognize and identify the capture of any image thatmatches one or more selectable parameters.

Furthermore, in another embodiment, analysis modules 540 mayadvantageously access image files 835 that have been processed andstored onto removable memory 354. Analysis modules 540 may thenautomatically categorize the image files 835 by analyzing image data 810and responsively generating corresponding category tags 735, inaccordance with the present invention.

In step 965, an image processing module 512 preferably performs asharpening procedure on image data 810, and also may perform a varietyof other processing options. Then, in step 970, an image processingmodule 512 preferably decimates image data 810. In the preferredembodiment, the decimation process reduces image resolution bydecimating the YCC 444 image data to produce YCC 422 or YCC 411 imagedata.

In step 975, the image data 810 is preferably compressed into a finalimage format (preferably JPEG.) Next, in step 980, file formatter 516preferably formats the compressed image file 835, and the resultingimage file 835 is finally saved into removable memory 354 in step 985.As discussed above, image file 835 thus includes any appropriatecategory tags which camera 110 may then subsequently automaticallyaccess to sort selected images, in accordance with the presentinvention.

The invention has been explained above with reference to a preferredembodiment. Other embodiments will be apparent to those skilled in theart in light of this disclosure. For example, the present invention mayreadily be implemented using configurations other than those describedin the preferred embodiment above. Additionally, the present inventionmay effectively be used in conjunction with systems other than the onedescribed above as the preferred embodiment. Therefore, these and othervariations upon the preferred embodiments are intended to be covered bythe present invention, which is limited only by the appended claims.

1. A digital camera that captures raw image data of a live view subject,the digital camera comprising: a processor within the digital camera forconverting the raw image data into processed image data at the time ofimage capture; an analysis module coupled to the processor andconfigured to analyze the raw image data at the time of the imagecapture in order to identify one or more categories to which each ofimages may relate and to automatically generate category tagscorresponding to the one or more identified categories; and theautomatically generated category tags attached by the analysis module tothe each of the images corresponding to the one or more identifiedcategories, the automatically generated category tags stored with eachof the images, thereby enabling the processor to automatically sort theimages into different categories.
 2. The digital camera of claim 1wherein the analysis module includes one or more analysis algorithms foridentifying the different categories.
 3. The digital camera of claim 2wherein the analysis module includes combination logic for combininganalysis results from the one or more analysis algorithms.
 4. Thedigital camera of claim 1 wherein the analysis module includesparametric controls for controlling the analysis module.
 5. The digitalcamera of claim 1 wherein the analysis module is selectively loaded intoa volatile memory from a removable memory.
 6. The digital camera ofclaim 1 further comprising a plurality of analysis modules.
 7. Thedigital camera of claim 1 wherein each of the images are stored as imagedata contained in individual image files.
 8. The digital camera of claim7 wherein the automatically generated category tags are stored with theimage data in the individual image files.
 9. The digital camera of claim1 further comprising an image processing backplane communicating withimage processing modules.
 10. The digital camera of claim 9 furthercomprising one or more insertion points between the image processingmodules for inserting the analysis module to analyze the images.
 11. Thedigital camera of claim 10 wherein a selectable plurality of analysismodules are inserted into the one or more insertion points.
 12. Thedigital camera of claim 10 further comprising an RGB insertion point anda YCC insertion point.
 13. The digital camera of claim 1 wherein theanalysis module is configured to recognize and label the images thatmatch predetermined criteria.
 14. The digital camera of claim 1 whereinthe analysis module is configured to access and categorize the imagesafter the images have been processed and stored into a storage device.15. The digital camera of claim 1 wherein the processor sorts the imagesby accessing and analyzing the category tags attached to each of theimages.
 16. The digital camera of claim 1 wherein the differentcategories include human images and nature images.
 17. The digitalcamera of claim 1 wherein the different categories include city imagesand water images.
 18. The digital camera of claim 1 further includingimage files for storing the processed image data, the image files havinglocations for image tags, wherein the image tags include capture tags.19. The digital camera of claim 1 wherein the category tags aregenerated by the analysis module after the analysis module examines theimage data.
 20. A method for automatically categorizing images in adigital camera that captures raw image data from a live view subject,the method comprising: converting the raw image data into processedimage data with a processor within the digital camera at the time ofimage capture; analyzing the raw image data with an analysis module atthe time of the image capture in order to identify one or morecategories to which each of images may relate; running the analysismodule with the processor; automatically generating category tagscorresponding to the one or more identified categories; attaching theautomatically generated category tags corresponding to the one or moreidentified categories to each of the images with the analysis module,thereby enabling the processor to automatically sort the images intodifferent categories; and storing the automatically generated categorytags with the images.
 21. The method of claim 20 wherein the analysismodule includes one or more analysis algorithms for identifying thedifferent categories.
 22. The method of claim 21 wherein the analysismodule includes combination logic for combining analysis results fromthe one or more analysis algorithms.
 23. The method of claim 20 whereinthe analysis module includes parametric controls for controlling theanalysis module.
 24. The method of claim 20 wherein the analysis moduleis selectively loaded into a volatile memory from a flash disk.
 25. Themethod of claim 20 further comprising a plurality of analysis modules.26. The method of claim 20 wherein the images each are stored as imagedata contained in individual image files.
 27. The method of claim 26wherein the automatically generated category tags are stored with theimage data in the individual image files.
 28. The method of claim 20further comprising an image processing backplane communicating withimage processing modules.
 29. The method of claim 28 further comprisingone or more insertion points between the image processing modules forinserting the analysis module to analyze the images.
 30. The method ofclaim 29 wherein a selectable plurality of analysis modules are insertedinto the one or more insertion points.
 31. The method of claim 29further comprising an RGB insertion point and a YCC insertion point. 32.The method of claim 20 wherein the analysis module is configured toinitially recognize and label the images that match predeterminedcriteria immediately upon capture of the images.
 33. The method of claim20 wherein the analysis module is configured to access and categorizethe images after the images have been processed and stored into astorage device.
 34. The method of claim 20 wherein the processor sortsthe images by accessing and analyzing the automatically generatedcategory tags attached to each of the images.
 35. The method of claim 20wherein the different categories include human images and nature images.36. The method of claim 20 wherein the different categories include cityimages and water images.
 37. A digital camera that captures raw imagedata from a live view subject, the digital camera comprising: means forconverting the raw image data into processed image data at the time ofimage capture, whereby the means for converting is within the digitalcamera; means for analyzing the raw image data at the time of the imagecapture in order to identify one or more categories to which each ofimages may relate; means for running the means for analyzing; means forautomatically generating category tags corresponding to the one or morecategories; means for attaching the automatically generated categorytags corresponding to the one or more categories to each of the images,thereby enabling the means for running to automatically sort the imagesinto different categories; and means for storing the automaticallygenerated category tags with each of the images.
 38. A non-volatilememory storing computer-readable program instructions for automaticallycategorizing images with a digital camera that captures raw image datafrom a live view subject, the program instructions for: converting theraw image data into processed image data at the time of image capturewith a processor within the digital camera; analyzing the raw image dataat the time of the image capture with an analysis module in order toidentify one or more categories to which each of images may relate;running the analysis module with the processor; automatically generatingcategory tags corresponding to the one or more categories; attaching theautomatically generated category tags corresponding to the one or morecategories to each of the images with the analysis module, therebyenabling the processor to automatically sort the images into differentcategories; and storing the automatically generated category tags witheach of the images.